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Speed up quantization processing on H3

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This commit is contained in:
Jaret Burkett
2026-08-03 15:21:39 -06:00
parent 88ac27fc8f
commit d3a3f70a2a
2 changed files with 49 additions and 5 deletions
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11
extensions_built_in/diffusion_models/minimax_h3/minimax_h3.py
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@@ -921,10 +921,12 @@ class MinimaxH3Model(BaseModel):
return ["blocks"]
def get_quantization_exclude_modules(self) -> Optional[List[str]]:
# float32 islands, the conditioning projection, and the token refiner
# (shipped bf16 in the pre-quantized checkpoints — excluding it makes
# quantize with the checkpoint's own qtype an exact no-op). The
# per-block adaln_proj stays quantizable (half the parameter count).
# float32 islands, the conditioning projection, the token refiner and
# the AdaLN projections — all shipped unquantized in the pre-quantized
# checkpoints (pruned files carry tiny fp16 adaln linears fed by the
# 8-dim time table), so excluding them makes quantize with the
# checkpoint's own qtype an exact no-op and keeps the sensitive
# modulation path at full precision under any other qtype.
return [
"video_patch_proj*",
"audio_patch_proj*",
@@ -932,6 +934,7 @@ class MinimaxH3Model(BaseModel):
"final_layer*",
"condition_proj*",
"token_refiner*",
"*adaln_proj*",
]
def convert_lora_weights_before_save(self, state_dict):